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510(k) Data Aggregation
(202 days)
The medical surgical masks are intended to be worn to protect both the patient and healthcare personnel from transfer of microorganisms, body fluids and particulate material. These masks are intended for use in infection control practices to reduce the potential exposure to blood and body fluids. This is a single use, disposable device(s), provided non-sterile.
The proposed device is a three-layer, flat pleated mask. Each mask is composed of a mask body, a nose piece and two ear loops. The mask body is manufactured with three layers, the inner layer and the outer layer are made of spunbond polypropylene nonwoven fabric, and the middle layer is made of meltblown polypropylene nonwoven fabric. The model of the proposed device, ear-loop, is held in place over the user's mouth and nose by two elastic ear loops welded to the mask body. The elastic ear loops are made of knitted elastic loops (made of nylon and spandex). The nose piece is in the layers of face mask to allow the user to fit the face mask around his nose, which is a galvanized wire with polyethylene covering. The proposed device is provided non-sterile and is intended to be a single use, disposable device.
This document describes the premarket notification (510(k)) for a Medical Surgical Mask (Non-sterile). The acceptance criteria and performance study details are provided in the "Non-clinical Testing" section, specifically in Table 2 "Performance Testing" and Table 3 "Biocompatibility Testing".
Here's the breakdown of the requested information:
1. Table of Acceptance Criteria and Reported Device Performance
The device is a medical surgical mask and its performance is evaluated against the ASTM F2100-19 standard for materials used in medical face masks. The acceptance criteria are specified for Level 1, Level 2, and Level 3 requirements, and the device reports performance that meets all these levels.
| Test | Purpose | Acceptance Criteria (ASTM F2100-19) | Reported Device Performance (Statistics of three lots) | Verdict |
|---|---|---|---|---|
| Fluid Resistance (ASTM F1862) | Verify the fluid resistance of the proposed device can simultaneously meet the requirements for Level 1, Level 2 and Level 3 specified in ASTM F2100-19. | Level 1: ≥29 out of 32 pass at 80 mmHg | 32 out of 32 pass at 80 mmHg | Pass |
| Level 2: ≥29 out of 32 pass at 120 mmHg | 32 out of 32 pass at 120 mmHg | Pass | ||
| Level 3: ≥29 out of 32 pass at 160 mmHg | 32 out of 32 pass at 160 mmHg | Pass | ||
| Bacterial Filtration Efficiency (BFE) (ASTM F2101) | Verify that bacterial filtration efficiency of the proposed device can simultaneously meet the requirements for Level 1, Level 2 and Level 3 specified in ASTM F2100-19. | Level 1: ≥95% | 99.56%~99.99% | Pass |
| Level 2: ≥98% | (Same as above) | Pass | ||
| Level 3: ≥98% | (Same as above) | Pass | ||
| Particulate Filtration Efficiency (PFE) (ASTM F2299) | Verify that particulate filtration efficiency of the proposed device can simultaneously meet the requirements for Level 1, Level 2 and Level 3 specified in ASTM F2100-19. | Level 1: ≥95% | 98.07%~99.24% | Pass |
| Level 2: ≥98% | (Same as above) | Pass | ||
| Level 3: ≥98% | (Same as above) | Pass | ||
| Differential Pressure (Delta-P) (EN 14683) | Verify that differential pressure of the proposed device can simultaneously meet the requirements for Level 1, Level 2 and Level 3 specified in ASTM F2100-19. | Level 1: < 5.0 mmH₂O/cm² | (3.4~3.9) mmH₂O/cm² | Pass |
| Level 2: < 6.0 mmH₂O/cm² | (Same as above) | Pass | ||
| Level 3: < 6.0 mmH₂O/cm² | (Same as above) | Pass | ||
| Flammability (16 CFR 1610) | Verify that Flammability of the proposed device can simultaneously meet the requirements for Level 1, Level 2 and Level 3 specified in ASTM F2100-19. | Level 1: Class 1 | Class 1 | Pass |
| Level 2: Class 1 | (Same as above) | Pass | ||
| Level 3: Class 1 | (Same as above) | Pass | ||
| Biocompatibility Testing (ISO 10993-5, -10) | In vitro Cytotoxicity: Verify that the proposed device extract is non-cytotoxic. | The extract is non-cytotoxic under the research conditions. | Pass | Pass |
| Skin Irritation: Verify that the proposed device extract is non-irritating. | The polar and non-polar extracts are non-irritating under the research conditions. | Pass | Pass | |
| Skin Sensitization: Verify that the proposed device extract is non-sensitizing. | The polar and non-polar extracts are non-sensitizing under the research conditions. | Pass | Pass |
2. Sample Size Used for the Test Set and Data Provenance
The document states "Results (Statistics of three lots)". This implies that the tests were performed on samples from three different production lots of the medical surgical mask. For Fluid Resistance, a sample size of 32 units (e.g., masks or material sections) per lot was used (as per 29 out of 32 requirement). The exact sample size for other tests like BFE, PFE, Differential Pressure, and Flammability is not explicitly stated as a number, but the results are reported as percentages or ranges, indicating testing on a sufficient number of samples to generate these statistics for each of the three lots.
The data provenance is China, as the applicant is Guangdong GoodFeeling Hygiene Material Tec Co., Ltd. located in China. The data is from non-clinical performance testing, which is inherently prospective testing specific to the device being submitted.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts
This section is not applicable as the study is a performance test of a physical device (medical mask) against established engineering and material standards, not a clinical study involving interpretation of data by human experts (like radiologists for AI models). The ground truth is the objective measurement defined by the respective ASTM, EN, and CFR standards.
4. Adjudication Method for the Test Set
This section is not applicable for the same reasons as #3. Adjudication methods (like 2+1, 3+1) are typically used in studies where human readers establish ground truth, e.g., in medical image interpretation.
5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study Was Done, If So, What Was the Effect Size of How Much Human Readers Improve with AI vs Without AI Assistance
This section is not applicable. The device is a medical mask, not an AI-assisted diagnostic tool or an imaging device. No MRMC study would be relevant for this type of product.
6. If a Standalone (i.e. algorithm only without human-in-the loop performance) Was Done
This section is not applicable. The device is a physical product (a medical mask), not an algorithm or software. Its performance is evaluated through laboratory tests, not algorithmic output.
7. The Type of Ground Truth Used
The ground truth for this medical device is based on established international and national consensus standards for medical face masks and biocompatibility:
- ASTM F2100-19: Standard Specification for Performance of Materials Used in Medical Face Masks.
- ASTM F1862/F1862M-17: Standard Test Method for Resistance of Medical Face Masks to Penetration by Synthetic Blood.
- ASTM F2101-19: Standard Test Method for Evaluating the Bacterial Filtration Efficiency (BFE) of Medical Face Mask Materials.
- ASTM F2299/F2299M-03(R2017): Standard Test Method for Determining the Initial Efficiency of Materials Used in Medical Face Masks to Penetration by Particulates.
- EN 14683:2019+AC:2019: Medical Face Masks - Requirements and Test Methods (specifically for Differential Pressure).
- 16 CFR 1610: Standard for the Flammability of Clothing Textiles.
- ISO 10993-1:2018, ISO 10993-5:2009, ISO 10993-10:2010: Biological evaluation of medical devices (for biocompatibility).
The "ground truth" is therefore derived from the quantitative measurements and qualitative observations (e.g., pass/fail for cytotoxicity) against the specified criteria within these recognized standards.
8. The Sample Size for the Training Set
This section is not applicable. As this is a physical medical device (mask) evaluated through performance and biocompatibility tests, there is no "training set" in the context of machine learning or AI models. The testing is for product verification against standards.
9. How the Ground Truth for the Training Set Was Established
This section is not applicable for the same reasons as #8.
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